HYPERSPECTRAL IMAGE COMPRESSION USING ENTROPY-CONSTRAINED PREDICTIVE TRELLIS-CODED QUANTIZATION

Authors
ABOUSLEMAN GP MARCELLIN MW HUNT BR
Citation
Gp. Abousleman et al., HYPERSPECTRAL IMAGE COMPRESSION USING ENTROPY-CONSTRAINED PREDICTIVE TRELLIS-CODED QUANTIZATION, IEEE transactions on image processing, 6(4), 1997, pp. 566-573
Citations number
28
Categorie Soggetti
Computer Sciences, Special Topics","Engineering, Eletrical & Electronic","Computer Science Software Graphycs Programming","Computer Science Theory & Methods
Journal title
IEEE transactions on image processing → ACNP
ISSN journal
10577149
Volume
6
Issue
4
Year of publication
1997
Pages
566 - 573
Database
ISI
SICI code
1057-7149(1997)6:4<566:HICUEP>2.0.ZU;2-O
Abstract
A training-sequence-based entropy-constrained predictive trellis coded quantization (ECPTCQ) scheme is presented for encoding autoregressive sources, For encoding a first-order Gauss-Markov source, the mean squ ared error (MSE) performance of an eight-state ECPTCQ system exceeds t hat of entropy-constrained differential pulse code modulation (ECDPCM) by up to 1.0 dB. In addition, a hyperspectral image compression syste m is developed, which utilizes ECPTCQ, A hyperspectral image sequence compressed at 0.125 b/pixel/band retains an average peak signal-to-noi se ratio (PSNR) of greater than 43 dB over the spectral bands.